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Rawalpindi, Pakistan

The Khan Research Laboratories, previously known at various times as Project-706, and Engineering Research Laboratories, is a Pakistan Government's multi-program national research institute, managed and operated under the scrutiny of Pakistan Armed Forces, located in Kahuta, Punjab Province. The laboratories are one of the largest science and technology institutions in Pakistan, and conducts multidisciplinary research and development in fields such as national security, space exploration, and supercomputing.While the laboratories remain highly classified, the KRL is most famous for its research, development, and production of Highly-Enriched Uranium , using gas-centrifuge technological methods roughly based on the model of the Urenco Group—the technology brought by Dr. Abdul Qadeer Khan, who worked there as a senior scientist. Since its inception, this institutes employed large number of technical staff members with majority being physicists and mathematicians, assisted by engineers , chemists, and material scientists. Professional scientists and engineers are also delegated to visit this institute after going under close and strict screening and background check, to participates as visitors in scientific projects.During the midst of the 1970s, the laboratories were the cornerstone of the first stage of Pakistan' atomic bomb project, being one of the various sites where the classified scientific research on atomic bombs were undertaken. Wikipedia.


Gramotnev D.K.,Khan Research Laboratories | Bozhevolnyi S.I.,University of Southern Denmark
Nature Photonics | Year: 2010

Recent years have seen a rapid expansion of research into nanophotonics based on surface plasmon-polaritons. These electromagnetic waves propagate along metal-dielectric interfaces and can be guided by metallic nanostructures beyond the diffraction limit. This remarkable capability has unique prospects for the design of highly integrated photonic signal-processing systems, nanoresolution optical imaging techniques and sensors. This Review summarizes the basic principles and major achievements of plasmon guiding, and details the current state-of-the-art in subwavelength plasmonic waveguides, passive and active nanoplasmonic components for the generation, manipulation and detection of radiation, and configurations for the nanofocusing of light. Potential future developments and applications of nanophotonic devices and circuits are also discussed, such as in optical signals processing, nanoscale optical devices and near-field microscopy with nanoscale resolution. © 2010 Macmillan Publishers Limited. All rights reserved. Source


Olver I.N.,Khan Research Laboratories
Current Opinion in Supportive and Palliative Care | Year: 2012

Purpose of review: This review updates the literature on hope and oncology following a prior review of studies up until 2009. It particularly focusses on the evolution of the definition of hope in the light of the clinical experience of patients with cancer, their carers and health professionals. Recent findings: Hope creates meaning for patients and is an important coping mechanism. Clinicians are wary of communicating bad news because it may deprive patients of hope, but work with decision aids suggests that this communication can be managed successfully. Hope and optimism negatively correlate with anxiety and depression. Maintaining hope may result in patients with incurable cancer accepting treatments or trials with little chance of benefit. Hope also needs to be maintained by palliative care nurses who harmonize their hopes with the different degrees and constructs of hope around them. Hope interventions can be successful in increasing hope and decreasing psychological distress. Summary: More research is required into how to communicate about active anticancer treatment withdrawal and prognosis without depriving patients with cancer of hope, given how important hope is in alleviating psychological distress. The optimal intervention to increase levels of hope needs further investigation. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins. Source


Jakob D.,Khan Research Laboratories
Australian Meteorological and Oceanographic Journal | Year: 2010

One of the main drivers for this project is the requirement to complement other high-quality surface data-sets with surface wind data for use in climate change detection and attribution studies. The high-quality data may also be used to analyse trends in storminess. Investigations highlighted the following three issues: Over the last two decades Automatic Weather Stations (AWS) have been installed at a large number of locations over the Australian region. The majority of newly installed wind instruments are rotating cup anemometers (Synchrotac), in many cases replacing older types, such as pressure tube anemometers (Dines). The corresponding changes in instrumentation alone can significantly change the characteristics of observed wind speed. Daylight Saving Time (DST) is in effect in the majority of Australian States, typically for a period from late October to late March. During this period, observations are taken according to DST rather than Local Standard Time (LST). Observations taken one hour earlier (compared with LST) can significantly affect the measured wind speed relative to climatology at a particular time. Estimates of daily mean wind speed depend on the frequency of synoptic observations. The frequency of these observations typically increases towards the latter part of the record, in some cases from two observations (at 0900 and 1500) to eight observations a day (at three-hourly intervals). Depending on the number of synoptic observations used to derive the daily mean wind speed, the true value may be significantly over- or underestimated. Source


Symonds M.R.E.,University of Melbourne | Moussalli A.,Khan Research Laboratories
Behavioral Ecology and Sociobiology | Year: 2011

Akaike's information criterion (AIC) is increasingly being used in analyses in the field of ecology. This measure allows one to compare and rank multiple competing models and to estimate which of them best approximates the "true" process underlying the biological phenomenon under study. Behavioural ecologists have been slow to adopt this statistical tool, perhaps because of unfounded fears regarding the complexity of the technique. Here, we provide, using recent examples from the behavioural ecology literature, a simple introductory guide to AIC: what it is, how and when to apply it and what it achieves. We discuss multimodel inference using AIC-a procedure which should be used where no one model is strongly supported. Finally, we highlight a few of the pitfalls and problems that can be encountered by novice practitioners. © 2010 Springer-Verlag. Source


Dane Panetta F.,Khan Research Laboratories
Diversity and Distributions | Year: 2012

Aim: To develop approaches to the evaluation of programmes whose strategic objectives are to halt or slow weed spread. Location: Australia. Methods: Key aspects in the evaluation of weed containment programmes are considered. These include the relevance of models that predict the effects of management intervention on spread, the detection of spread, evidence for containment failure and metrics for absolute or partial containment. Case studies documenting either near-absolute (Orobanche ramosa L., branched broomrape) or partial (Parthenium hysterophorus (L.) King and Robinson, parthenium) containment are presented. Results: While useful for informing containment strategies, predictive models cannot be employed in containment programme evaluation owing to the highly stochastic nature of realized weed spread. The quality of observations is critical to the timely detection of weed spread. Effectiveness of surveillance and monitoring activities will be improved by utilizing information on habitat suitability and identification of sites from which spread could most compromise containment. Proof of containment failure may be difficult to obtain. The default option of assuming that a new detection represents containment failure could lead to an underestimate of containment success, the magnitude of which will depend on how often this assumption is made. Main conclusions: Evaluation of weed containment programmes will be relatively straightforward if containment is either absolute or near-absolute and may be based on total containment area and direct measures of containment failure, for example, levels of dispersal, establishment and reproduction beyond (but proximal to) the containment line. Where containment is only partial, other measures of containment effectiveness will be required. These may include changes in the rates of detection of new infestations following the institution of interventions designed to reduce dispersal, the degree of compliance with such interventions, and the effectiveness of tactics intended to reduce fecundity or other demographic drivers of spread. © 2012 Blackwell Publishing Ltd. Source

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